code: def get_perturbations(
      tokens: Sequence[str],
      masks: np.ndarray,
      mask_token: str = "<unk>",
  ) -> Iterable[str]:
      """Returns strings with the masked tokens replaced with `mask_token`."""
      for mask in masks:
          parts = [
              t if mask[i] else mask_token for i, t in enumerate(tokens)
          ]
          yield " ".join(parts)
  
file_path: lit/lit_nlp/components/citrus/lime.py
imports: from collections.abc import Callable, Iterable, Sequence
  import functools
  from typing import Any, Optional
  from lit_nlp.components.citrus import helpers
  from lit_nlp.components.citrus import utils
  import numpy
  from sklearn import linear_model
  from sklearn import metrics
label_desc: Use image node_id 2 for calling a global function with example usage: get_perturbations(tokens, masks, mask_token) without return types